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Bayesian network based sentence retrieval model

Published: 08 May 2007 Publication History

Abstract

This paper makes an intensive investigation of the application of Bayesian network in sentence retrieval and introduces three Bayesian network based sentence retrieval models with or without consideration of term relationships. Term relationships in this paper are considered from two perspectives: relationships between pairs of terms and relationships between terms and term sets. Experiments have proven the efficiency of Bayesian network in the application of sentence retrieval. Particularly, retrieval result with consideration of the second kind of term relationship performs better in improving retrieval precision.

References

[1]
Grahne, G., Zhu, J. Efficiently using prefix-trees in mining frequent itemsets. In proceedings of ICDM 2003 Workshop on Frequent Itemset Mining Implementations (FIMI'03) (Melbourne, FL, USA, Dec. 19, 2003).
[2]
Lund, K., Burgess, C. Producing High dimensional Semantic Spaces from Lexical Co-occurrence. Behavior Research Methods, Instruments, & Computers, 28, 2 (1996), 203--208.
[3]
Pearl, J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann (1988)

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  1. Bayesian network based sentence retrieval model

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    cover image ACM Conferences
    WWW '07: Proceedings of the 16th international conference on World Wide Web
    May 2007
    1382 pages
    ISBN:9781595936547
    DOI:10.1145/1242572
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    New York, NY, United States

    Publication History

    Published: 08 May 2007

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    Author Tags

    1. Bayesian network
    2. sentence retrieval
    3. term relationship

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    WWW'07
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    WWW'07: 16th International World Wide Web Conference
    May 8 - 12, 2007
    Alberta, Banff, Canada

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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